Revolutionizing IT Operations with GenAI and Agentic AI

Emerging technologies like generative AI (GenAI) and agentic AI are poised to significantly enhance IT operations. These advancements offer new, truly transformative ways to manage, optimize and automate IT environments, and are certain to improve efficiency and foster innovation.

GenAI’s ability to process vast amounts of unstructured data and agentic AI’s autonomous decision-making capabilities span predictive analytics to automated problem-solving. These technologies are not simply enhancing existing processes but actually redefining the very foundation of IT management.

What Is AIOps?

The term AIOps was introduced by Gartner nearly a decade ago, initially standing for algorithmic IT operations. The company’s approach to AIOps involved applying algorithmic analysis to large datasets. Over time, the definition evolved to the more familiar artificial intelligence for IT operations.

For solutions to qualify in the AIOps category today, they must encompass an AI technology stack that includes components such as machine learning for pattern detection/alert correlation, anomaly detection, and behavioral analysis. Additionally, AIOps solutions expanded to include intelligent process automation, which automates routine tasks, thereby improving incident response. The goal of AIOps is to create a comprehensive data set, give structure to unstructured data and analyze it for patterns to automate processes based on those insights.

Watch our new webinar to learn more GenAI, agentic AI and AIOps

As IT operations contend with complex, hybrid cloud environments, large data volumes, false positives and poor integration, the challenge can be further intensified by an aging data center workforce nearing retirement. This necessitates doing more with less. Consequently, organizations are rapidly adopting emerging technologies – such as GenAI – to tackle these issues effectively.

Emerging Trends in AIOps

A few years ago, when ChatGPT burst onto the scene, it became impossible to discuss AIOps without mentioning GenAI. While it takes time for such technologies to mature, we’re now seeing their early integration into our technology stacks. One reason is that GenAI excels at handling vast amounts of unstructured data, such as system logs, incident reports and technical documentation. This capability enables AIOps systems to identify patterns and anomalies, determine likely root causes, and suggest solutions based on historical data and real-time analysis.

Working collaboratively with our partner Virtana, we brought this capability to Hitachi EverFlex Control. The result was a GenAI copilot to assist with:

• Troubleshooting Alerts: Providing expanded alert recommendations for improved meantime detection.
• Automated Root Cause Analysis: AI-driven analysis quickly pinpoints the underlying cause of any issue.
• Configuration Management: An AI assistant helps manage configurations efficiently.

As GenAI continues to evolve, it will play a larger role in predictive analytics, forecasting potential issues before they occur. It can detect anomalies and trigger automated responses, ensuring that problems are addressed swiftly and efficiently.

Agentic AI Takes AIOps to Another Level

Plato once said, “The beginning of wisdom is the definition of terms.” As we navigate the early stages of emerging technologies like GenAI and agentic AI, the definitions of these terms can sometimes be broad and nuanced.

My colleague (and our CTO for Artificial Intelligence) Jason Hardy recently described agentic AI as an army of experts ready to help us conduct business. But for the purposes of this blog, I’ll use a more specific definition focused on autonomous process automation.

Over the past 25 years, I've had the privilege of witnessing the evolution of IT process automation firsthand. It started with simple workflows, progressed to workflow automation, then to business process management and ultimately to business process automation.

About 10 years ago, robotic process automation (RPA) emerged, excelling at automating repetitive tasks with structured data. We then integrated AI technologies like natural language processing (NLP) into RPA bots to structure data, enhancing RPA's effectiveness. This later became known as intelligent process automation.

Now, we're seeing the rise of AI agents that incorporate some autonomous decision-making and goal-oriented tasks. All these technologies represent rules-based automation, requiring programming to function effectively.

However, agentic AI is characterized by being goal-oriented and designed to achieve specific objectives, capable of making complex decisions and handling intricate tasks independently without requiring human input. Additionally, it can adapt and improve over time based on its experiences, much like humans do. 

Sample Agentic AIOps Use Case

Here’s an example of how agentic AIOps supports IT Operations.

• Monitoring and Alerts: Monitors IT operations for alerts and decides when an event needs to be created in the IT service management system (ITSM).
• Automated Ticketing: Creates an automated ticket, populating it with all gathered information and potential resolution steps.
• Alert Correlation: Recognizes additional alerts related to the initial one and automatically correlates them.
• Team Notification: Notifies the necessary team member of the alert status and executes process automation to resolve or heal the issue.
• Learning and Adaptation: If it encounters a problem resolving the event, it can reach out to a manager for guidance, learning and adapting for future issue resolution.

The key here is that agentic AI operates entirely without human programming or intervention. While this might sound like Jarvis, Tony Stark’s AI assistant from the Marvel movies, we’re already seeing practical applications in industries such as healthcare, finance and manufacturing.

Explore Agentic AI Operations Management with Hitachi

At Hitachi Vantara, we’re committed to advancing GenAI and agentic AI. We are working with companies like Zetaris, a leading AI development company, to bring agentic AI to the forefront for our customers. Combined with Hitachi iQ, our new portfolio of data infrastructure and solutions designed for the AI market, we’re poised to usher in the next era of AI-led IT operations.

Watch our recent webinar, AIOps Driven Infrastructure Consumption Services, which focuses on Hitachi EverFlex Control and Hyperautomation for the IT Enterprise, and connect with your Hitachi Vantara representative to learn more.

Read more

• Webinar: Revolutionizing IT Operations with AIOps
• Webpage: Deliver Continuous Insights, Intelligence and Automation with EverFlex Control
• Solution Brief: Hitachi EverFlex Infrastructure as a Service Portfolio
• Blog: IT Infrastructure Modernization for Business Agility with Hitachi EverFlex
• Blog: Five Major Ways Agentic AI Will Change IT & Data Management